get_num_fits.optimal_feature_selection_learner

Julia Equivalent:
<a href="https://docs.interpretable.ai/v3.2.2/OptimalFeatureSelection/reference/#IAI.get_num_fits-Tuple%7BOptimalFeatureSelectionLearner%7D"><code>IAI.get_num_fits</code></a>

An interface to the algorithms of 'Interpretable AI'
<https://www.interpretable.ai> from the R programming language.
'Interpretable AI' provides various modules, including 'Optimal Trees' for
classification, regression, prescription and survival analysis, 'Optimal
Imputation' for missing data imputation and outlier detection, and 'Optimal
Feature Selection' for exact sparse regression. The 'iai' package is an
open-source project. The 'Interpretable AI' software modules are proprietary
products, but free academic and evaluation licenses are available.

Jack Dunn

Interface to 'Interpretable AI' Modules

Ying Zhuo

Interpretable AI LLC 

get_num_fits.optimal_feature_selection_learner function

<dl><dt>obj</dt>
<dd>The Optimal Feature Selection learner to query.</dd>
<dt>...</dt>
<dd>Additional arguments (unused)</dd></dl>

Arguments

Requires IAI version 3.0 or higher.

IAI Compatibility

Julia Equivalent:
<a href='https://docs.interpretable.ai/v3.2.2/OptimalFeatureSelection/reference/#IAI.get_num_fits-Tuple%7BOptimalFeatureSelectionLearner%7D'><code>IAI.get_num_fits</code></a>

Return the number of fits along the path in a trained Optimal Feature
Selection learner — get_num_fits.optimal_feature_selection_learner

<dl>

<dt>obj</dt>
<dd>The Optimal Feature Selection learner to query.</dd>


<dt>...</dt>
<dd>Additional arguments (unused)</dd>

</dl>

Requires IAI version 3.0 or higher.

get_num_fits.optimal_feature_selection_learner: Return the number of fits along the path in a trained Optimal Feature Selection learner

Description

Usage

Arguments

IAI Compatibility

Examples